Hindawi Publishing Corporation
Journal of Diabetes Research
Volume 2015, Article ID 157201, 9 pages
http://dx.doi.org/10.1155/2015/157201
Review Article
Effects of Glucagon-Like Peptide-1 Receptor
Agonists on Weight Loss in Patients with Type 2 Diabetes:
A Systematic Review and Network Meta-Analysis
Feng Sun,1,2 Sanbao Chai,3 Lishi Li,1,4 Kai Yu,5 Zhirong Yang,1,6 Shanshan Wu,1
Yuan Zhang,1 Linong Ji,7 and Siyan Zhan1
1
Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre,
38 Xueyuan Road, Haidian District, Beijing 100191, China
2
Department of Preventive Medicine, College of Medicine, Shihezi University, Shihezi 832002, China
3
Department of Physiology, Capital Medical University, Beijing 100069, China
4
Department of Statistics, Graduate School of Arts and Sciences, Columbia University, New York, NY 10027, USA
5
Department of Orthopedics, Tianjin Fifth Central Hospital, Tianjin 300450, China
6
Shantou-Oxford Clinical Research Unit, Shantou University Medical College, Shantou 515041, China
7
Department of Endocrinology and Metabolism, People’s Hospital, Peking University, Beijing 100044, China
Correspondence should be addressed to Kai Yu; [email protected] and Siyan Zhan; [email protected]
Received 18 September 2014; Revised 12 December 2014; Accepted 22 December 2014
Academic Editor: Mitsuhiko Noda
Copyright © 2015 Feng Sun et al. This is an open access article distributed under the Creative Commons Attribution License, which
permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
To evaluate the effectiveness of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) on weight reduction in patients with
Type 2 diabetes mellitus (Type 2 DM), a network meta-analysis was conducted. MEDLINE, EMBASE, Cochrane Library, and
ClinicalTrials.gov were searched from 1950 to October 2013. Randomized controlled trials (RCTs) involving GLP-1 RAs were
included if they provided information on body weight. A total of 51 RCTs were included and 17521 participants were enrolled. The
mean duration of 51 RCTs was 31 weeks. Exenatide 10 𝜇g twice daily (EX10BID) reduced weight compared with exenatide 5 𝜇g twice
daily (EX5BID), liraglutide 0.6 mg once daily (LIR0.6QD), liraglutide—1.2 mg once daily (LIR1.2QD), and placebo treatment, with
mean differences of −1.07 kg (95% CI: −2.41, −0.02), −2.38 kg (95% CI: −3.71, −1.06), −1.62 kg (95% CI: −2.79, −0.43), and −1.92 kg
(95% CI: −2.61, −1.24), respectively. Reductions of weight treated with liraglutide—1.8 mg once daily (LIR1.8QD) reach statistical
significance (−1.43 kg (95% CI: −2.73, −0.15)) versus LIR1.2QD and (−0.98 kg (95% CI: −1.94, −0.02)) versus placebo. Network
meta-analysis found that EX10BID, LIR1.8QD, and EX2QW obtained a higher proportion of patients with weight loss than other
traditional hypoglycemic agents. Our results suggest GLP-1 RAs are promising candidates for weight control in comparison with
traditional hypoglycemic drugs, and EX10BID, LIR1.8QD, and EX2QW rank the top three drugs.
1. Introduction
Glucagon-like peptide-1 (GLP-1) is a gut hormone, secreted
from the intestine in response to meal ingestion, which
stimulates insulin secretion and inhibits glucagon release in a
dose-dependent fashion [1]. GLP-1 can suppress food intake
and appetite and decelerate gastric emptying and induce
satiety, so it plays an important role in regulation of blood
glucose [2, 3]. But the rapid inactivation of GLP-1 in vivo and
the consequent short half-life prevents its therapeutic use.
Long acting GLP-1 receptor agonists (GLP-1 RAs) that can
be administered via subcutaneous injection once or twice a
day or even once a week have been developed [4]. GLP-1 RAs
include exenatide, liraglutide, albiglutide, taspoglutide, lixisenatide and LY2189265. Treatment with GLP-1 RAs improves
insulin resistance and glucose homoeostasis for patients with
Type 2 DM [5, 6]. Also they have a rather low risk of
hypoglycemia because of their mode of action. Exenatide and
liraglutide are currently successfully being employed in the
treatment of Type 2 DM [7].
2
Overweight or obesity may increase the risk of cardiovascular complications as well as resulting in serious
psychological distress for most patients with Type 2 DM [8].
Effective interventions designed to achieve weight reduction
are a critical part of Type 2 DM management to prevent the
development of microvascular and macrovascular complications. But many antidiabetic agents (insulin, thiazolidinediones, and sulfonylureas) have side-effect of bodyweight
increase. GLP-1 can stimulate satiety by binding to its receptor
on hypothalamic neurons and reduce calorie ingestion by
delayed gastric emptying [9, 10]. Although several metaanalyses have revealed the association between GLP-1 RAs
and weight loss, all of them are head-to-head comparisons of
GLP-1 RAs versus placebo or active comparator drugs [7, 11–
13], and these analyses did not evaluate the impact of different
doses of GLP-1 RAs on weight loss. Therefore, we did network
meta-analysis of GLP-1 RAs in order to provide up-to-date
overview of the effects of GLP-1 RAs on weight control in
patients with Type 2 DM.
2. Materials and Methods
2.1. Search Strategy. In consultation with a medical librarian, we established a search strategy for the MEDLINE,
EMBASE, and Cochrane Library (from 1950 to October 2013).
The following search strategy (Ovid) was adapted for the
other databases: (1) exp glucagon-like peptide-1 agonists/;
(2) (glucagon-like peptide∗ or GLP-1).tw.; (3) (exenatide or
liraglutide).tw.; (4) randomized controlled trial.pt.; (5) (randomized or randomised).tw.; (6) ((1) or (2) or (3)) and ((4)
or (5)). We also searched ClinicalTrials.gov for (unpublished)
completed trials. In addition, we searched the bibliographies
of published systematic reviews [7, 11–13]. All relevant authors
and principal investigators were contacted to supplement
incomplete reports of the original papers or to provide data
for unpublished studies.
Journal of Diabetes Research
2 mg once weekly (EX2QW). The standard liraglutide regimens are 0.6 mg once daily (LIR0.6QD), 0.9 mg once daily
(LIR0.9QD), 1.2 mg once daily (LIR1.2QD), and 1.8 mg once
daily (LIR1.8QD), respectively.
2.4. Data Extraction and Quality Evaluation. After obtaining
full reports of the candidate trials, two reviewers (CSB and
LLS) independently used ADDIS software [14] to extract
information concerning population characteristics (age, T2D
course, baseline HbA1c ) and weight change of each treatment
group. Quality of studies was assessed according to JADAD
scale [15]: adequate method for randomization, appropriate
blinding procedures, and detailed report of withdrawals. We
resolved differences in extraction through discussion and
consensus.
2.5. Data Analysis
2.5.1. Methods for Direct Treatment Comparisons. Initially,
we performed standard pairwise meta-analyses using the
DerSimonian-Laird random effects model [16] for every
treatment comparison. Where studies did not report intentto-treat, we analyzed outcomes as all-patients randomized.
The 𝐼2 statistic was calculated as a measure of the proportion
of the overall variation that is attributable to between-study
heterogeneity [17].
2.2. Inclusion and Exclusion Criteria. All the studies included
are in English and they are eligible for inclusion only if they
were RCTs involving GLP-1 RAs, other hypoglycemic drugs
or placebo with complete data on body weight. Trials are
excluded if only they meet one of the following: (1) trials
are not RCT (e.g., review, expert comment, editor opinion,
new agent introduction, single case report, or case series); (2)
early studies; (3) experimentation on animals or in vitro; (4)
not conducted in Type 2DM; (5) pharmacokinetics research;
(6) trials underway, unfinished, or suspended; (7) economical
evaluation research; (8) other unrelated researches. These
studies were approved by the local ethics committees and
written informed consent was obtained from all the patients.
2.5.2. Network Meta-Analysis. We did a network metaanalysis within a Bayesian framework [18], and we summarized the results using mean difference (MD) and credible
interval (CrI). Bayesian network meta-analysis was a generalization of traditional meta-analysis that allowed all evidence
to be taken into account simultaneously (both direct and indirect). We estimated the posterior densities for all unknown
parameters using MCMC (Markov chain Monte Carlo) for
each model. Each chain used 40,000 iterations with a burnin of 20,000. To formally check whether a model’s overall fit
was satisfactory, we considered an absolute measure of fit:
𝐷res . This is the posterior mean of the deviance under the
current model, minus the deviance for the saturated model.
We would expect that each data point should contribute about
1 to the posterior mean deviance so that it can be compared
with the number of data points for the purpose of checking
model fit [19]. We estimated the ranking probabilities for all
treatments at each possible rank for every intervention. Then,
we obtained a treatment hierarchy using the surface under
the cumulative ranking curve (SUCRA) [20] and posterior
mean ranks. SUCRA can also be expressed as a percentage
interpreted as the percentage of efficacy of a treatment on
weight control that would be ranked first without uncertainty.
2.3. Clinical Doses of GLP-1 RAs. We only included doses that
are likely to be used in routine clinical care. We excluded
trials or arms using nonstandard doses, which mainly
came from dose-ranging studies. So only those dosearms possibly relevant to clinical application were included
in our study. The standard exenatide regimens are 5 𝜇g
twice daily (EX5BID), 10 𝜇g twice daily (EX10BID), and
2.5.3. Assessment of Statistical Inconsistency. One key
assumption of the network meta-analysis models is the
consistency between direct and indirect evidence, that is,
if the information of both sources of evidence is similar
enough in order to be combined. To evaluate the presence of
inconsistency locally we will use the loop-specific approach
[21]. This method evaluates the consistency assumption
Journal of Diabetes Research
3
Medline: n = 322
Embase: n = 553
Cochrane: n = 231
Total: n = 1106
ClinicalTrial.gov:
n = 33
Duplicated: n = 1
Duplicated: n = 368
n = 738
Exclusion reasons:
Exclusion reasons:
Review or letter: n = 187
Not RCT: n = 313
Non-T2DM: n = 52
No GLP-1 treatment: n = 76
No relevant outcomes: n = 61
Mixed treatment of GLP-1: n = 2
Duplicated: n = 2
Not RCT: n = 5
No relevant outcomes: n = 6
Non-T2DM patients: n = 1
Duplicated with publication:
n = 18
Obtained by hand search: n = 4
Included: n = 2
Included: n = 49
Trials included: n = 51
Figure 1: Flowchart of inclusion and exclusion.
in each closed loop of the network separately as the
difference between direct and indirect estimates for a specific
comparison in the loop (inconsistency factor). Then, the
magnitude of the inconsistency factors and their 95% CIs can
be used to infer the presence of inconsistency in each loop.
Inconsistency can be evaluated as the disagreement between
different sources of evidence within a closed loop [22].
Analyses were conducted using STATA 11.0 (pairwise
meta-analysis, 𝐼2 calculations, and estimation of inconsistence), R 3.0.2 (SUCRA graphs) and WinBUGS 1.4.3 (network
meta-analysis and model fit).
3. Results
3.1. Literature Search Results and Study Characteristics. 1139
studies were identified at first. Finally, 51 studies involving 13
treatments and 17521 participants with a mean duration of 31
weeks were included. Flowchart of inclusion and exclusion
was showed in Figure 1.
3.1.1. Study Characteristics. Table 1 summarized the characteristics of the included 51 studies. Publication year varied
from 2002 to 2013 and duration ranged from 4 weeks to
234 weeks. The 17521 patients had a mean baseline HbA1c of
8.3%, a mean age of 56 y, and a mean diabetes duration of
8.3 y. There were 36 studies about exenatide, 13 studies about
liraglutide, and 2 studies for both [23, 24].
3.1.2. Evidence Network. Thirteen treatments were analyzed,
including seven GLP-1 RAs dose-group (EX10BID, EX2QW,
EX5BID, LIR0.6QD, LIR0.9QD, LIR1.2QD, and LIR1.8QD),
five kinds of traditional antidiabetics (insulin, metformin
(Met), sulfonylureas (SU), sitagliptin, and thiazolidinediones
(TZD)), and placebo. Thirty-two trials (62.75%) were twoarm studies and nineteen (37.25%) were multiple-arm studies
(see Table 1 and Figure 2), totally 127 arms. The maximum
studies about EX10BID were fourteen.
3.1.3. Methodological Quality of Studies. We found that the
reporting quality of studies varied. The overall quality of
studies was rated according to JADAD scale. The proportion
of appropriate description of randomization, allocation concealment, blinding, and dropout were 78.43% (40/51), 50.98%
(26/51), 52.94% (27/51), and 88.24% (45/51), respectively.
Additionally, 90.20% (46/51) trials were used intention-totreat analysis (see Table 1 in Supplementary Material available
online at http://dx.doi.org/10.1155/2015/157201). Overall risk
of bias was, respectively, low and bias mainly came from
allocation concealment and blinding of outcome assessment.
3.2. Direct Pairwise Meta-Analysis and
Network Meta-Analysis
3.2.1. Direct Pairwise Meta-Analysis about the Impact of GLP1 RAs on Weight Control. Table 2 shows the outcome of
direct meta-analysis. Compared with placebo, EX10BID and
LIR1.8QD decreased body weight by −1.38 kg (95% CI: −1.74,
−1.03) and −1.32 kg (95% CI: −2.22, −0.43), respectively, while
there was a statistically significant weight gain observed in
the traditional hypoglycemic drugs (insulin, SU, and TZD)
compared with placebo, with mean differences of 2.02 kg
(95% CI: 1.02, 3.02), 2.03 kg (95% CI: 0.91, 3.15), and 2.20 kg
(95% CI: 1.54, 2.86), respectively.
4
Journal of Diabetes Research
Table 1: Characteristics of the studies included in the network meta-analysis.
Study ID
Investigational treatments
Size
Therapy
duration
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
Apovian CM, 2010
Arnolds S, 2010
Barnett AH, 2007
Bergenstal R, 2009
Bunck MC, 2009
Buse JB, 2004
Buse JB, 2011
DURATION-1, Drucker DJ, 2008
DURATION-2, Bergenstal RM, 2010
DURATION-3, Diamant M, 2012
DURATION-4, Russell-JonesD, 2012
DURATION-6, Buse JB, 2013
Davies M, 2013
Davies MJ, 2009
Davis SN, 2007
DeFronzo RA, 2005
DeFronzo RA, 2010
Derosa G, 2010
Derosa G, 2011
Derosa G, 2012
Forst T, 2012
Gallwitz B, 2011
Gallwitz B, EUREXA, 2012
Gao Y, 2009
Harder H, 2004
Heine RJ, 2005
Inagaki N, 2012
Iwamoto K, 2009
Ji LN, 2013
Kadowaki T, 2009
Kadowaki T, 2011
Kaku K, 2010
Kendall DM, 2005
Kim D, 2007
142
48
276
248
69
377
259
295
491
466
820
802
194
204
45
336
88
116
101
171
40
354
386
466
33
535
426
19
574
114
178
264
733
29
24
4
16
24
52
30
30
30
26
84
26
26
26
26
16
30
20
52
52
48
12
26
234
16
8
26
26
10
26
12
24
52
30
15
35
LEAD-1 Marre M, 2009
1041
26
56.1
6.5
8.4
36
LEAD-2 Nauck M, 2009
1077
104
57
7.9
8.4
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
LEAD-3 Garder A, 2011
LEAD-4 Zinman B, 2009
LEAD-5 Russell-Jones D, 2009
LEAD-6-Buse JB, 2009
Liutkus J, 2010
Moretto TJ, 2008
NCT00620282, 2011
NCT00701935, 2013
Nauck MA, 2007
Pratley R, 2011
Seino Y, 2008
Seino Y, 2010
Yang W, 2011
Yuan GH, 2012
Zinman B, 2007
EX10BID, placebo
EX10BID, placebo, and sitagliptin
EX10BID, insulin
EX10BID, insulin
EX10BID, insulin
EX5BID, EX10BID, and placebo
EX10BID, placebo
EX10BID, EX2QW
EX2QW, sitagliptin, and TZD
EX2QW, insulin
EX2QW, sitagliptin, Met, and TZD
EX2QW, LIR1.8
EX2QW, insulin
EX10BID, insulin
EX10BID, insulin
EX5BID, EX10BID, and placebo
EX10BID, TZD
EX10BID, SU
EX10BID, SU
EX10BID, placebo
LIR1.8, placebo
EX10BID, insulin
EX10BID, SU
EX10BID, placebo
LIR0.6, placebo
EX10BID, insulin
EX2QW, insulin
EX2QW, placebo
EX10BID, EX2QW
EX5BID, placebo, and EX10BID
EX5BID, EX10BID, and placebo
LIR0.9, LIR0.6, and placebo
EX5BID, EX10BID, and placebo
EX2QW, placebo
LIR1.2, LIR0.6, LIR1.8, TZD, and
placebo
LIR1.2, LIR0.6, LIR1.8, SU, and
placebo
LIR1.2, LIR1.8, and SU
LIR1.2, LIR1.8, and placebo
LIR1.8, insulin, and placebo
EX10BID, LIR1.8
EX10BID, placebo
EX5BID, EX10BID, and placebo
LIR1.8, SU, and placebo
EX10BID, placebo
EX10BID, insulin
LIR1.2, LIR1.8, and sitagliptin
LIR0.6, LIR0.9, and placebo
LIR0.9, SU
LIR0.6, LIR1.2, LIR1.8, and SU
EX10BID, Met
EX10BID, and placebo
Baseline information
Course of
Age
HbA1c
T2D
54.8
5.5
7.6
56.5
5.5
8.2
54.9
7.4
9
52.2
8.5
10.2
58.3
4.9
7.5
55
6.3
8.6
59
12
8.4
55
6.5
8.3
52.5
6
8.6
58
7.9
8.3
53.8
2.7
8.5
57
—
8.5
58.5
—
8.4
56.5
8.7
8.6
53
11
8.1
53
5.8
8.2
56
4.7
7.8
56.5
—
8.9
55.5
—
8.8
57.0
7.7
8.0
55.1
3.8
6.3
57
5
7.9
56
5.8
—
54.5
8
8.3
60
4.1
7.5
58.9
9.6
8.2
56.76
9.03
8.5
58
6
7.4
55
—
—
60.3
11.8
8
58.4
12
8.2
59.7
10.3
8.4
55.3
8.9
8.5
54
5
8.5
733
533
576
464
165
232
47
75
501
644
135
400
907
59
233
104
26
26
26
26
24
12
24
52
52
14
52
16
26
16
53
55
57.6
56.7
54.7
54
58.5
58.2
58.5
55.3
57
58.3
53.3
50.5
56
5.4
9
9.4
8.2
6.4
2
6.8
57.9
9.9
6.2
8
8.3
7.5
<1 month
8
8.3
8.5
8.3
—
8.2
7.8
7.2
—
8.6
8.4
8.3
8.9
8.5
8.2
7.9
Number
Note: LEAD: liraglutide effect and action in diabetes; DURATION: diabetes therapy utilization: researching changes in HbA1c , weight, and other factors
through intervention with exenatide once weekly; EX5BID: exenatide 5 𝜇g twice daily; EX10BID: exenatide 10 𝜇g twice daily; EX2QW: exenatide 2 mg once
weekly; LIR0.6: liraglutide 0.6 mg once daily; LIR0.9: liraglutide 0.9 mg once daily; LIR1.2: liraglutide 1.2 mg once daily; LIR1.8: liraglutide 1.8 mg once daily;
SU: sulfonylureas; TZD: thiazolidinediones; Met: metformin. —: unavailable information.
Journal of Diabetes Research
5
EX10BID
EX2QW
Placebo
TZD
EX5BID
Sitagliptin
Insulin
SU
LIR0.6
Met
LIR0.9
LIR1.8
LIR1.2
Figure 2: Network of clinical trials about GLP-1 RAs and other hypoglycemic drugs or placebo in patients with Type 2 diabetes. Lines
connect the interventions that have been studied in head-to-head (direct) comparisons in the eligible RCTs. The width of the lines represents
the cumulative number of RCTs for each pairwise comparison and the size of every node is proportional to the number of randomized
participants (sample size). EX5BID: exenatide 5 𝜇g twice daily; EX10BID: exenatide 10 𝜇g twice daily; EX2QW: exenatide 2 mg once weekly;
LIR0.6: liraglutide 0.6 mg once daily; LIR0.9: liraglutide 0.9 mg once daily; LIR1.2: liraglutide 1.2 mg once daily; LIR1.8: liraglutide 1.8 mg once
daily; SU: sulfonylureas; TZD: thiazolidinediones; Met: metformin.
GLP-1 RAs achieved a greater weight loss than traditional
hypoglycemic drugs; the range of weight reduction was
−7.30 kg (95% CI: −12.82, −1.78)∼−1.38 kg (95% CI: −1.74,
−1.03) with exenatide and −3.12 kg (95% CI: −3.80, −2.44)∼
−1.40 kg (95% CI: −1.95, −0.85) with liraglutide, respectively.
3.2.2. Network Meta-Analysis about the Impact of GLP-1 RAs
on Weight Control. Table 2 displays the result of network
meta-analysis between GLP-1 RAs and traditional hypoglycemic drugs. As displayed in the preceding pairwise metaanalysis, we found EX10BID and LIR1.8QD were associated
with a significant reduction in body weight versus placebo,
with mean differences of −1.92 kg (95% CI: −2.61, −1.24) and
−0.98 kg (95% CI: −1.94, −0.02), respectively, while treatment
with insulin, SU, and TZD resulted in significant weight gain
versus placebo (range from 2.60 kg (95% CI: 1.56, 3.62) to
3.37 kg (95% CI: 2.29, 4.48)).
Similar to direct comparisons, exenatide and liraglutide
showed more advantage on weight control than traditional
hypoglycemic drugs. The weight reduction significantly
ranged from −5.30 kg (95% CI: −6.38, −4.24) to −2.21 kg (95%
CI: −3.59, −0.83) with exenatide and from −4.35 kg (95% CI:
−5.45, −3.24) to −2.21 kg (95% CI: −3.92, −0.53) with liraglutide.
Compared with EX5BID, LIR0.6QD, LIR1.2QD, and placebo treatment, treatment with EX10BID resulted in a significantly greater decrease in body weight, with mean differences
of −1.07 kg (95% CI: −2.41, −0.02), −2.38 kg (95% CI: −3.71,
−1.06), −1.62 kg (95% CI: −2.79, −0.43), and −1.92 kg (95% CI:
−2.61, −1.24), respectively. Reductions in body weight treated
with LIR1.8QD reach statistical significance (−1.43 kg (95%
CI: −2.73, −0.15)) versus LIR0.6QD and (−0.98 kg (95% CI:
−1.94, −0.02)) versus placebo.
3.3. Ranking of Different Doses of GLP-1 RAs on Weight
Control. Network meta-analyses enable estimation of the
probability that each intervention is the best for each outcome. Probabilities for each treatment can be plotted in
absolute rankograms or cumulative rankograms. A simple
numerical summary supplying the graphical display of cumulative ranking is used to estimate the surface under the
cumulative line for each treatment. Larger SUCRA means the
drug has lower ranking (see Supplementary Figures 1(a) and
1(b)).
Table 3 showed the mean SUCRA values providing the
hierarchy of 13 treatments on weight loss: EX10BID (98.30%),
LIR1.8QD (78.89%), EX2QW (76.23%), EX5BID (75.02%),
Met (63.32%), LIR1.2QD (58.44%), placebo (48.50%),
LIR0.9QD (42.90%), sitagliptin (42.47%), LIR0.6QD
(38.83%), insulin (12.86%), TZD (11.29%), and SU (3.02%),
respectively. According to SUCRA values, EX10BID had the
highest impact and SU had the least impact on weight loss
among 13 treatments.
3.4. Model Fit and Inconsistency Check. The model fit can be
evaluated using the posterior mean of the residual deviance
𝐷res . The value of the 𝐷res was 115.41, close to 127 of the data
points for weight control, meaning model’s overall fit was
relatively satisfactory. Additionally, statistical inconsistency
2.91 kg
(1.51, 4.29)
0.06 kg
(−1.14, 1.26)
−0.43 kg
(−2.41, 1.53)
−0.95 kg
(−1.93, 0.03)
−1.44 kg
(−3.32, 0.45)
−3.53 kg
(−5.23, −1.85)
−0.86 kg
(−1.90, 0.20)
−4.59 kg
−3.59 kg
(−5.99, −3.24) (−5.04, −2.16)
−1.92 kg
(−2.61, −1.24)
2.60 kg
(1.56, 3.62)
—
0.46 kg
(0.11, 0.81)
0.68 kg
(−0.40, 1.74)
LIR1.2QD
LIR1.8QD
—
—
—
—
—
—
—
—
0.95 kg
(−1.32, 3.18)
3.37 kg
(2.29, 4.48)
0.70 kg
(−0.92, 2.27)
3.09 kg
(1.49, 4.69)
SU
—
−3.12 kg
(−3.80, −2.44)
−2.94 kg
(−3.74, −2.14)
−2.27 kg
(−3.11, −1.42)
−2.11 kg
(−6.01, 1.79)
—
—
0.28 kg
(−1.09, 1.67)
−2.38 kg
(−3.95,
−0.80)
Sitagliptin
—
−1.62 kg
(−2.48,
−0.76)
−2.52 kg
(−3.38,
−1.66)
−1.20 kg
(−2.26,
−0.14)
—
—
—
—
−0.79 kg
(−2.06, 0.48)
−0.50 kg
(−1.09, 0.09)
2.02 kg
(1.02, 3.02)
0.33 kg
(−0.22, 0.89)
0.49 kg
(−3.63, 4.60)
−1.27 kg
(−5.72, 3.18)
−1.38 kg
(−1.74, −1.03)
2.67 kg
(1.28, 4.07)
Placebo
2.20 kg
(1.54, 2.86)
−0.30 kg
(−1.37, 0.77)
−2.94 kg
(−4.21, −1.67)
TZD
2.03 kg
(0.91, 3.15)
—
—
−3.50 kg
(−4.56, −2.44)
−2.30 kg
−1.32 kg
(−2.85, −1.75) (−2.22, −0.43)
−1.80 kg
(−2.35, −1.25)
—
−1.40 kg
(−1.95, −0.85)
—
—
−1.99 kg
−7.30 kg
−1.00 kg
−4.30 kg
(−2.77, −1.21) (−12.82, −1.78) (−2.14, 0.14) (−5.82, −2.78)
−1.38 kg
−4.33 kg
0.00 kg
—
(−2.06,
(−5.90, −2.77)
(−1.25, 1.25)
−0.70)
0.54 kg
(0.23, 0.85)
—
0.89 kg
(0.39, 1.39)
0.37 kg
(−0.55, 1.29)
3.40 kg
(2.49, 4.31)
0.74 kg
(0.42, 1.05)
—
—
—
1.06 kg
0.17 kg
−0.49 kg
Met
(−2.50,
(−1.97, 2.33)
(−2.55, 1.51)
4.66)
−2.92 kg
−2.82 kg
−3.68 kg
−4.35 kg
−3.87 kg
(−4.27,
(−5.85,
(−4.92, −2.48) (−5.45, −3.24) (−5.99, −1.73)
−1.53)
0.29)
0.16 kg
0.27 kg
−0.59 kg
−1.26 kg
−0.77 kg
(−1.55, 1.93) (−3.01, 3.61) (−2.17, 0.97)
(−2.72, 0.19)
(−2.87, 1.32)
−2.21 kg
−2.11 kg
−2.98 kg
−3.65 kg
−3.16 kg
(−3.92,
(−5.31, 1.23) (−4.56, −1.41) (−5.13, −2.19) (−5.26, −1.09)
−0.53)
0.56 kg
0.46 kg
−0.31 kg
−0.98 kg
−0.49 kg
(−2.48,
(−0.80, 1.71)
(−1.44, 0.81) (−1.94, −0.02) (−2.45, 1.46)
3.68)
1.43 kg
1.53 kg
(0.15, 2.73) (−1.50, 4.73)
0.76 kg
0.87 kg
(−0.60, 2.12) (−2.24, 4.11)
−0.10 kg
LIR0.9QD
(−3.24, 2.95)
0.70 kg
(−3.19, 4.59)
—
—
—
—
Treatments are reported in alphabetical order. For data above the cells marked with underlined data, comparisons between treatments should be read from left to right and the estimate is in the cell in common
between the column-defining treatment and the row-defining treatment; for data under the cells marked with underlined data, it is reverse order to read the results. EX5BID: exenatide 5 𝜇g twice daily; EX10BID:
exenatide 10 𝜇g twice daily; EX2QW: exenatide 2 mg once weekly; LIR0.6: liraglutide 0.6 mg once daily; LIR0.9: liraglutide 0.9 mg once daily; LIR1.2: liraglutide 1.2 mg once daily; LIR1.8: liraglutide 1.8 mg once
daily; SU: sulfonylureas; TZD: thiazolidinediones; Met: metformin.
−0.92 kg
(−2.01, 0.13)
2.31 kg
(0.76, 3.85)
−1.14 kg
(−2.83, 0.55)
−2.21 kg
−1.20 kg
(−3.59, −0.83) (−2.64, 0.23)
−0.07 kg
(−1.62, 1.47)
−0.77 kg
(−2.12, 0.55)
3.10 kg
(1.06, 5.11)
3.58 kg
(2.39, 4.78)
−5.30 kg
−4.29 kg
−4.23 kg
(−6.38, −4.24) (−5.66, −2.91) (−5.65, −2.79)
−0.37 kg
(−2.52, 1.74)
0.12 kg
(−1.24, 1.47)
−0.55 kg
(−2.03, 0.93)
—
Insulin
LIR0.6QD
—
—
—
—
−0.61 kg
(−2.01, 0.75)
−3.17 kg
(−5.48, −0.85)
−4.77 kg
(−5.48, −4.05)
−1.62 kg
(−2.79, −0.43)
—
−0.66 kg
(−1.11, −0.21)
2.14 kg
(0.63, 3.65)
2.04 kg
(−1.19, 5.16)
EX2QW
−0.61 kg
(−1.37, 0.15)
−1.07 kg
−0.07 kg
EX5BID
(−2.14, −0.02) (−1.47, 1.32)
−4.52 kg
−3.53 kg
−3.46 kg
(−5.39, −3.65) (−4.62, −2.44) (−4.78, −2.11)
−2.38 kg
−1.38 kg
−1.31 kg
(−3.71, −1.06) (−2.91, 0.13)
(−2.91, 0.29)
−2.48 kg
−1.48 kg
−1.40 kg
(−5.65, 0.53)
(−4.74, 1.67)
(−4.70, 1.77)
−1.00 kg
(−2.01, 0.03)
EX10BID
Table 2: Results of network meta-analysis (data under the cells marked with underlined data) and direct comparison (data above the cells marked with underlined data) of all treatments.
6
Journal of Diabetes Research
Journal of Diabetes Research
7
Table 3: Mean differences of weight and the rank of GLP-1 RAs on
weight loss in comparison with placebo.
Treatment
EX10BID
EX2QW
EX5BID
LIR0.6
LIR0.9
LIR1.2
LIR1.8
Insulin
Met
SU
Sitagliptin
TZD
Placebo
Weight control
MD (95% CI)
SUCRA
−1.92 (−2.61, −1.24)
0.98298
−0.92 (−2.01, 0.13)
0.76228
−0.86 (−1.90, 0.20)
0.75020
0.46 (−0.80, 1.71)
0.38829
0.56 (−2.48, 3.68)
0.42898
−0.31 (−1.44, 0.81)
0.58441
−0.98 (−1.94, −0.02)
0.78891
2.60 (1.56, 3.62)
0.12863
−0.49 (−2.45, 1.46)
0.63318
3.37 (2.29, 4.48)
0.03021
0.28 (−1.09, 1.67)
0.42465
2.67 (1.28, 4.07)
0.11287
Reference
0.48504
Rank
1
3
4
10
8
6
2
11
5
13
9
12
7
Note: EX5BID: exenatide 5 𝜇g twice daily; EX10BID: exenatide 10 𝜇g twice
daily; EX2QW: exenatide 2 mg once weekly; LIR0.6: liraglutide 0.6 mg
once daily; LIR0.9: liraglutide 0.9 mg once daily; LIR1.2: liraglutide 1.2 mg
once daily; LIR1.8: liraglutide 1.8 mg once daily; SU: sulfonylureas; TZD:
thiazolidinediones; Met: metformin.
between direct and indirect comparisons was generally low
for weight control. Most loops (90.70%, 39/43) of 27 triangular loops and 16 quadratic loops were consistent (𝑃 value >
0.05; see Supplementary Table 2) and their 95% CIs included
0 according to the forest plots; that means the direct estimate
of the summary effect was not different from the indirect
estimate (see Supplementary Figure 2).
4. Discussion
Obesity is known to increase the risk of diabetes and
complications such as insulin resistance, dyslipidemia, and
cardiovascular diseases [25, 26]. Over 80% of individuals with
Type 2 DM are overweight or obese [27]. It is attractive to
both doctors and patients to avoid weight gain of Type 2
DM during the treatment of glycaemic control. GLP-1 RAs
are a novel class of glucose-lowering drugs which has been
shown to improve glycaemic control and promote weight loss
in clinical studies of patients with Type 2 DM. In 2005, the US
Food and Drug Administration approved the first long acting
stable GLP-1 RA. Exenatide (Byetta; EliLilly) and liraglutide
(Victoza; NovoNordisk) are now available on the market.
Both drugs can be used in combination with oral antidiabetic
drugs such as metformin, thiazolidinediones, or sulfonylureas compounds. The treatments are approved for patients
with Type 2 DM who have not achieved adequate glycemic
control after treatment with traditional antidiabetic drugs.
The network meta-analysis combines direct and indirect
evidences in a single analysis, enabling simultaneously comparison of multiple interventions, which is different from the
traditional meta-analysis. This approach makes use of direct
comparisons from existing trials comparing 2 treatment
strategies and indirect comparisons constructed from 2 trials
that have at least 1 treatment in common [18]. This statistical
tool preserves the within-trial, randomized comparison of
each study. And Bayesian posterior probabilities were used
to classify the effect of GLP-1 RAs.
Our study showed that a higher proportion of subjects
experienced weight loss with exenatide (EX10BID, EX2QW,
and EX5BID) and liraglutide (LIR1.2QD, LIR0.6QD, and
LIR1.8QD) than with insulin, SU, and TZD, which were
similar to previous meta-analysis [7, 11–13, 28], with weight
loss following GLP-1 RAs treatment ranging from −3.31
to −1.22 kg. Our results indicated that subjects experienced greater weight reductions in a higher exenatide dose
(EX10BID) and liraglutide dose (LIR1.8QD) compared with
insulin, SU, TZD, and placebo, suggesting a dose-dependent
effect. In accordance with the previous report liraglutide
1.8 mg treated subjects experienced more weight loss than
1.2 mg treated subjects [29]. Compared with placebo, treatment with SU, TZDs, and insulin resulted in a significantly
greater increase in body weight, with change from 2.60 kg to
3.37 kg. By contrast, use of EX10BID and LIR1.8QD resulted
in a significant decrease in bodyweight, with mean changes
of −1.92 kg and −0.98 kg, respectively. These results were
consistent with the previous studies [30–33]. Although the
precise mechanisms associated with weight loss have not been
elucidated yet, it was believed that gastric emptying was an
important factor for weight loss. However, the preclinical
study showed that liraglutide’s effect on gastric emptying
diminished over time, whereas the effect on body weight
was sustained over the treatment period. Recently, evidence
indicated that GLP-1-induced weight reduction required
higher GLP-1 RAs levels [34].
Compared with placebo, weight did not decrease substantially either with EX2QW and EX5BID or with LIR0.6QD,
LIR0.9QD, and LIR1.2QD. But the results suggested the
potential relationship between weight reduction and drug
dose. Except for EX10BID, body weight loss was not significant for sitagliptin and GLP-1 RAs in our meta-analysis. Like
the report that showed subjects taking metformin alone lost
more weight than subjects taking an SU plus metformin [35],
our study showed that body weight did not change in patients
with metformin compared with those with exenatide and
liraglutide.
There were statistically and clinically significant differences between drug classes in weight changes. In our study,
EX10BID, LIR1.8QD, and EX2QW were ranked the top three
drugs in terms of weight reduction. The results suggested
weight reduction of patients has a close relationship with dose
of GLP-1 RAs.
There are several strengths in our analysis. First, our study
is the largest evaluation of GLP-1 RAs on weight control to
date. Second, the network meta-analysis technique allows
dissection of the individual drug to evaluate weight control,
especially facing very few RCTs which directly compared
GLP-1 RAs in Type 2 DM. We applied a Bayesian model to
explore the effect of indirect comparison between them, and
it is thought to be the most appropriate method for multipletreatments network meta-analysis [18]. Additionally, posterior probability from Bayesian model can help to apply the
rank of GLP-1 RAs in practice.
8
Several limitations need to be cautious. First, other
unpublished literatures on relevant pharmaceutical websites
were not searched and only trials in English were included,
which may lead to a potential publication bias. Second, most
trials included in this review were not specially designed to
evaluate body weight, with the risk of misdiagnosis and under
diagnosis. Finally, lack of information about the distribution
of clinical and methodological variables may lead to potential
sources of either heterogeneity or inconsistency in every
comparison-specific group of trials.
To sum up, this network meta-analysis provides a useful
and complete picture of the associations between GLP-1
RAs, conventional antidiabetic drugs, and placebo on weight
control. GLP-1 RAs are associated with significant weight loss
for the treatment of Type 2 DM. However, the application of
our results should take into account limitations of the analysis
and the specific clinical situation. More long-term largescale trials will be necessary to confirm potential efficacy
on weight loss. Meantime, determining the specific subjectrelated factors associated with greater weight loss with GLP-1
receptor agonists may be helpful to clinicians in identifying
patients who would likely benefit from their use.
5. Conclusions
GLP-1 receptor agonists cause weight reduction, in contrast
to insulin, metformin, sulfonylureas, sitagliptin, thiazolidinediones, and placebo. According to the mean SUCRA values,
EX10BID, LIR1.8QD, and EX2QW rank the top three drugs.
Conflict of Interests
The authors declare that they have no competing interests.
Authors’ Contribution
Feng Sun and Siyan Zhan designed the study and revised the
paper, Lishi Li and Kai Yu extracted the data, Shanshan Wu
and Zhirong Yang evaluated the RCTs quality, Yuan Zhang
and Sanbao Chai verified the data, Feng Sun and Sanbao
Chai researched the data and wrote the paper, and Linong Ji
and Siyan Zhan contributed to interpreting the results, draft
reviewing, and finalizing the paper. Feng Sun and Sanbao
Chai contributed equally to this work.
Acknowledgments
This study is funded by National Natural Science Foundation of China (81302508), Research Fund for the Doctoral
Program of Higher Education (20120001110015), the Doctoral
Fund of Corps (2010JC15), and Health Bureau of Binhai
New Area Science and Technology Projects (2012BWKZ002,
2011BHKY008). The authors are grateful to all cooperating
organizations and their staff whose hard work made this study
possible. Special thanks to all of the original study authors
who promptly and graciously responded to our requests
for information. Siyan Zhan and Kai Yu will become the
cocorresponding authors.
Journal of Diabetes Research
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http://www.hindawi.com
Volume 2014
Oxidative Medicine and
Cellular Longevity
Hindawi Publishing Corporation
http://www.hindawi.com
Volume 2014